论文标题
AI及以后的无服务器编程范式和完整的堆栈自动化的情况 - Jaseci和Jac的理念
The Case for a Wholistic Serverless Programming Paradigm and Full Stack Automation for AI and Beyond -- The Philosophy of Jaseci and Jac
论文作者
论文摘要
在这项工作中，该案例是为了对系统堆栈的全面自上而下的重新启动，从编程语言级别通过系统体系结构降低了这一复杂性差距。我们设计的关键目的是解决程序员在问题水平上以更高级别的抽象表达解决方案的关键需求，同时拥有运行时系统堆栈并隐藏广泛的扩散子应用程序范围，并掩盖了弥漫性子应用程序和机间资源。这项工作还介绍了这种系统堆栈体系结构的生产级实现，称为JASECI，以及相应的编程语言JAC。 JAC和JASECI已作为开放源代码发布，并由实际产品团队利用，以加速和部署复杂的AI产品和其他应用程序。 JAC已在商业生产环境中使用，将AI开发时间表加速了约10倍，Jaseci运行时自动化决策和优化通常属于在团队中的手动工程角色范围，例如应该和不应是微服务和动态变化的团队。
In this work, the case is made for a wholistic top-down re-envisioning of the system stack from the programming language level down through the system architecture to bridge this complexity gap. The key goal of our design is to address the critical need for the programmer to articulate solutions with higher level abstractions at the problem level while having the runtime system stack subsume and hide a broad scope of diffuse sub-applications and inter-machine resources. This work also presents the design of a production-grade realization of such a system stack architecture called Jaseci, and corresponding programming language Jac. Jac and Jaseci has been released as open source and has been leveraged by real product teams to accelerate developing and deploying sophisticated AI products and other applications at scale. Jac has been utilized in commercial production environments to accelerate AI development timelines by ~10x, with the Jaseci runtime automating the decisions and optimizations typically falling in the scope of manual engineering roles on a team such as what should and should not be a microservice and changing those dynamically.
